Overview

Brought to you by YData

Dataset statistics

Number of variables21
Number of observations23151
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 MiB
Average record size in memory168.0 B

Variable types

Numeric10
DateTime1
Text4
Categorical5
Boolean1

Alerts

condition has constant value "New" Constant
currency has constant value "USD" Constant
disc_percentage is highly overall correlated with is_saleHigh correlation
disc_price is highly overall correlated with price and 1 other fieldsHigh correlation
is_sale is highly overall correlated with disc_percentage and 1 other fieldsHigh correlation
merchant is highly overall correlated with is_saleHigh correlation
month is highly overall correlated with month_n and 1 other fieldsHigh correlation
month_n is highly overall correlated with month and 1 other fieldsHigh correlation
price is highly overall correlated with disc_price and 1 other fieldsHigh correlation
price_std is highly overall correlated with disc_price and 1 other fieldsHigh correlation
week_number is highly overall correlated with month and 1 other fieldsHigh correlation
is_sale is highly imbalanced (67.8%) Imbalance
unnamed: 0 has unique values Unique
cluster has 509 (2.2%) zeros Zeros
disc_percentage has 21795 (94.1%) zeros Zeros

Reproduction

Analysis started2025-04-12 19:23:45.227008
Analysis finished2025-04-12 19:24:04.878046
Duration19.65 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

unnamed: 0
Real number (ℝ)

Unique 

Distinct23151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15338.318
Minimum4
Maximum29592
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:04.975457image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile1686.5
Q17897.5
median15613
Q322678
95-th percentile28226.5
Maximum29592
Range29588
Interquartile range (IQR)14780.5

Descriptive statistics

Standard deviation8528.8056
Coefficient of variation (CV)0.55604568
Kurtosis-1.2028157
Mean15338.318
Median Absolute Deviation (MAD)7342
Skewness-0.071744278
Sum3.5509741 × 108
Variance72740526
MonotonicityStrictly increasing
2025-04-12T16:24:05.154565image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
29592 1
 
< 0.1%
4 1
 
< 0.1%
5 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
12 1
 
< 0.1%
Other values (23141) 23141
> 99.9%
ValueCountFrequency (%)
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
11 1
< 0.1%
12 1
< 0.1%
13 1
< 0.1%
ValueCountFrequency (%)
29592 1
< 0.1%
29591 1
< 0.1%
29590 1
< 0.1%
29589 1
< 0.1%
29588 1
< 0.1%
29587 1
< 0.1%
29586 1
< 0.1%
29585 1
< 0.1%
29584 1
< 0.1%
29583 1
< 0.1%
Distinct188
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size181.0 KiB
Minimum2017-01-05 00:00:00
Maximum2017-12-22 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-04-12T16:24:05.323423image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:05.497623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

cluster
Real number (ℝ)

Zeros 

Distinct58
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.682735
Minimum0
Maximum57
Zeros509
Zeros (%)2.2%
Negative0
Negative (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:05.669838image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q18
median20
Q335
95-th percentile49
Maximum57
Range57
Interquartile range (IQR)27

Descriptive statistics

Standard deviation15.576818
Coefficient of variation (CV)0.68672575
Kurtosis-1.0103014
Mean22.682735
Median Absolute Deviation (MAD)14
Skewness0.31231821
Sum525128
Variance242.63727
MonotonicityNot monotonic
2025-04-12T16:24:05.833142image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 2130
 
9.2%
20 1715
 
7.4%
35 1104
 
4.8%
42 1072
 
4.6%
9 865
 
3.7%
3 817
 
3.5%
15 744
 
3.2%
37 719
 
3.1%
6 718
 
3.1%
31 712
 
3.1%
Other values (48) 12555
54.2%
ValueCountFrequency (%)
0 509
 
2.2%
1 406
 
1.8%
2 570
 
2.5%
3 817
 
3.5%
4 239
 
1.0%
5 2130
9.2%
6 718
 
3.1%
7 203
 
0.9%
8 247
 
1.1%
9 865
3.7%
ValueCountFrequency (%)
57 280
1.2%
56 225
1.0%
55 121
 
0.5%
54 48
 
0.2%
53 129
 
0.6%
52 142
 
0.6%
51 87
 
0.4%
50 100
 
0.4%
49 87
 
0.4%
48 407
1.8%
Distinct58
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:06.144812image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length31
Median length26
Mean length20.465466
Min length7

Characters and Unicode

Total characters473796
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowspeaker, portable, bluetooth
2nd rowspeaker, portable, bluetooth
3rd rowspeaker, portable, bluetooth
4th rowspeaker, portable, bluetooth
5th rowspeaker, portable, bluetooth
ValueCountFrequency (%)
computer 4143
 
6.6%
speaker 4068
 
6.5%
camera 3578
 
5.7%
tv 2508
 
4.0%
home 2448
 
3.9%
audio 2171
 
3.5%
video 2130
 
3.4%
television 2130
 
3.4%
laptop 1954
 
3.1%
car 1922
 
3.1%
Other values (84) 35651
56.9%
2025-04-12T16:24:06.574616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 58369
12.3%
39552
 
8.3%
, 39552
 
8.3%
r 39176
 
8.3%
o 38410
 
8.1%
a 35881
 
7.6%
t 27429
 
5.8%
p 22086
 
4.7%
i 20287
 
4.3%
s 18964
 
4.0%
Other values (15) 134090
28.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 473796
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 58369
12.3%
39552
 
8.3%
, 39552
 
8.3%
r 39176
 
8.3%
o 38410
 
8.1%
a 35881
 
7.6%
t 27429
 
5.8%
p 22086
 
4.7%
i 20287
 
4.3%
s 18964
 
4.0%
Other values (15) 134090
28.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 473796
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 58369
12.3%
39552
 
8.3%
, 39552
 
8.3%
r 39176
 
8.3%
o 38410
 
8.1%
a 35881
 
7.6%
t 27429
 
5.8%
p 22086
 
4.7%
i 20287
 
4.3%
s 18964
 
4.0%
Other values (15) 134090
28.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 473796
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 58369
12.3%
39552
 
8.3%
, 39552
 
8.3%
r 39176
 
8.3%
o 38410
 
8.1%
a 35881
 
7.6%
t 27429
 
5.8%
p 22086
 
4.7%
i 20287
 
4.3%
s 18964
 
4.0%
Other values (15) 134090
28.3%

name
Text

Distinct908
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:06.919614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length200
Median length104
Mean length62.30517
Min length8

Characters and Unicode

Total characters1442427
Distinct characters87
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond
2nd rowBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond
3rd rowBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond
4th rowBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond
5th rowBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond
ValueCountFrequency (%)
22921
 
9.5%
black 6199
 
2.6%
with 4748
 
2.0%
wireless 2378
 
1.0%
bluetooth 2324
 
1.0%
smart 2288
 
1.0%
camera 2277
 
0.9%
speaker 2145
 
0.9%
led 2100
 
0.9%
tv 2045
 
0.9%
Other values (2385) 190605
79.4%
2025-04-12T16:24:07.611752image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
216947
 
15.0%
e 98088
 
6.8%
a 74999
 
5.2%
r 63721
 
4.4%
o 60738
 
4.2%
i 56922
 
3.9%
t 54482
 
3.8%
l 47321
 
3.3%
s 39960
 
2.8%
- 39297
 
2.7%
Other values (77) 689952
47.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1442427
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
216947
 
15.0%
e 98088
 
6.8%
a 74999
 
5.2%
r 63721
 
4.4%
o 60738
 
4.2%
i 56922
 
3.9%
t 54482
 
3.8%
l 47321
 
3.3%
s 39960
 
2.8%
- 39297
 
2.7%
Other values (77) 689952
47.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1442427
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
216947
 
15.0%
e 98088
 
6.8%
a 74999
 
5.2%
r 63721
 
4.4%
o 60738
 
4.2%
i 56922
 
3.9%
t 54482
 
3.8%
l 47321
 
3.3%
s 39960
 
2.8%
- 39297
 
2.7%
Other values (77) 689952
47.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1442427
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
216947
 
15.0%
e 98088
 
6.8%
a 74999
 
5.2%
r 63721
 
4.4%
o 60738
 
4.2%
i 56922
 
3.9%
t 54482
 
3.8%
l 47321
 
3.3%
s 39960
 
2.8%
- 39297
 
2.7%
Other values (77) 689952
47.8%

price
Real number (ℝ)

High correlation 

Distinct3023
Distinct (%)13.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean513.0378
Minimum1
Maximum10879.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:07.765382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile33.99
Q182.99
median199.99
Q3540
95-th percentile2034.99
Maximum10879.95
Range10878.95
Interquartile range (IQR)457.01

Descriptive statistics

Standard deviation859.11
Coefficient of variation (CV)1.674555
Kurtosis34.411146
Mean513.0378
Median Absolute Deviation (MAD)140.11
Skewness4.5951604
Sum11877338
Variance738070
MonotonicityNot monotonic
2025-04-12T16:24:07.947347image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.99 519
 
2.2%
199.99 496
 
2.1%
149.99 435
 
1.9%
59.99 394
 
1.7%
399.99 324
 
1.4%
129.99 315
 
1.4%
79.99 311
 
1.3%
299.99 294
 
1.3%
49.99 287
 
1.2%
249.99 259
 
1.1%
Other values (3013) 19517
84.3%
ValueCountFrequency (%)
1 19
0.1%
1.5 1
 
< 0.1%
2 6
 
< 0.1%
2.99 2
 
< 0.1%
3 3
 
< 0.1%
6.45 1
 
< 0.1%
6.99 6
 
< 0.1%
7.45 1
 
< 0.1%
7.95 1
 
< 0.1%
7.98 1
 
< 0.1%
ValueCountFrequency (%)
10879.95 2
 
< 0.1%
10503.6 1
 
< 0.1%
10499.99 31
0.1%
6999.99 12
 
0.1%
6499.99 8
 
< 0.1%
5738 4
 
< 0.1%
5499.99 6
 
< 0.1%
5199.99 27
0.1%
5010.5 2
 
< 0.1%
5006 1
 
< 0.1%

disc_price
Real number (ℝ)

High correlation 

Distinct3174
Distinct (%)13.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean494.1043
Minimum1
Maximum10879.95
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:08.127046image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile32.99
Q179.99
median199
Q3516.49
95-th percentile1999
Maximum10879.95
Range10878.95
Interquartile range (IQR)436.5

Descriptive statistics

Standard deviation808.58897
Coefficient of variation (CV)1.6364743
Kurtosis39.612839
Mean494.1043
Median Absolute Deviation (MAD)140.01
Skewness4.7483485
Sum11439009
Variance653816.13
MonotonicityNot monotonic
2025-04-12T16:24:08.301743image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
99.99 499
 
2.2%
199.99 464
 
2.0%
149.99 431
 
1.9%
59.99 388
 
1.7%
399.99 321
 
1.4%
129.99 315
 
1.4%
79.99 311
 
1.3%
49.99 279
 
1.2%
299.99 272
 
1.2%
69.99 251
 
1.1%
Other values (3164) 19620
84.7%
ValueCountFrequency (%)
1 19
0.1%
1.5 1
 
< 0.1%
2 6
 
< 0.1%
2.99 2
 
< 0.1%
3 3
 
< 0.1%
6.45 1
 
< 0.1%
6.99 6
 
< 0.1%
7.45 1
 
< 0.1%
7.95 1
 
< 0.1%
7.98 1
 
< 0.1%
ValueCountFrequency (%)
10879.95 2
 
< 0.1%
10503.6 1
 
< 0.1%
10499.99 31
0.1%
6499.99 1
 
< 0.1%
5499.99 6
 
< 0.1%
5296 3
 
< 0.1%
5010.5 2
 
< 0.1%
5006 1
 
< 0.1%
4999.99 6
 
< 0.1%
4998 4
 
< 0.1%

merchant
Categorical

High correlation 

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size181.0 KiB
Bestbuy.com
11287 
bhphotovideo.com
5064 
Walmart.com
3947 
ebay.com
2809 
Amazon.com
 
25
Other values (2)
 
19

Length

Max length16
Median length11
Mean length11.727398
Min length8

Characters and Unicode

Total characters271501
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWalmart.com
2nd rowWalmart.com
3rd rowWalmart.com
4th rowWalmart.com
5th rowWalmart.com

Common Values

ValueCountFrequency (%)
Bestbuy.com 11287
48.8%
bhphotovideo.com 5064
21.9%
Walmart.com 3947
 
17.0%
ebay.com 2809
 
12.1%
Amazon.com 25
 
0.1%
kmart.com 17
 
0.1%
barcodable.com 2
 
< 0.1%

Length

2025-04-12T16:24:08.470472image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-12T16:24:08.594941image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
bestbuy.com 11287
48.8%
bhphotovideo.com 5064
21.9%
walmart.com 3947
 
17.0%
ebay.com 2809
 
12.1%
amazon.com 25
 
0.1%
kmart.com 17
 
0.1%
barcodable.com 2
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
o 38370
14.1%
m 27140
10.0%
c 23153
 
8.5%
. 23151
 
8.5%
t 20315
 
7.5%
b 19164
 
7.1%
e 19162
 
7.1%
y 14096
 
5.2%
u 11287
 
4.2%
s 11287
 
4.2%
Other values (14) 64376
23.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 271501
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 38370
14.1%
m 27140
10.0%
c 23153
 
8.5%
. 23151
 
8.5%
t 20315
 
7.5%
b 19164
 
7.1%
e 19162
 
7.1%
y 14096
 
5.2%
u 11287
 
4.2%
s 11287
 
4.2%
Other values (14) 64376
23.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 271501
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 38370
14.1%
m 27140
10.0%
c 23153
 
8.5%
. 23151
 
8.5%
t 20315
 
7.5%
b 19164
 
7.1%
e 19162
 
7.1%
y 14096
 
5.2%
u 11287
 
4.2%
s 11287
 
4.2%
Other values (14) 64376
23.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 271501
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 38370
14.1%
m 27140
10.0%
c 23153
 
8.5%
. 23151
 
8.5%
t 20315
 
7.5%
b 19164
 
7.1%
e 19162
 
7.1%
y 14096
 
5.2%
u 11287
 
4.2%
s 11287
 
4.2%
Other values (14) 64376
23.7%

condition
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size181.0 KiB
New
23151 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters69453
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNew
2nd rowNew
3rd rowNew
4th rowNew
5th rowNew

Common Values

ValueCountFrequency (%)
New 23151
100.0%

Length

2025-04-12T16:24:08.749887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-12T16:24:08.817886image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
new 23151
100.0%

Most occurring characters

ValueCountFrequency (%)
N 23151
33.3%
e 23151
33.3%
w 23151
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 69453
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 23151
33.3%
e 23151
33.3%
w 23151
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 69453
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 23151
33.3%
e 23151
33.3%
w 23151
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 69453
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 23151
33.3%
e 23151
33.3%
w 23151
33.3%

disc_percentage
Real number (ℝ)

High correlation  Zeros 

Distinct68
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.016933178
Minimum0
Maximum0.8
Zeros21795
Zeros (%)94.1%
Negative0
Negative (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:08.930059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.11
Maximum0.8
Range0.8
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.07784918
Coefficient of variation (CV)4.5974347
Kurtosis28.75492
Mean0.016933178
Median Absolute Deviation (MAD)0
Skewness5.2176319
Sum392.02
Variance0.0060604948
MonotonicityNot monotonic
2025-04-12T16:24:09.116992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 21795
94.1%
0.07 72
 
0.3%
0.17 56
 
0.2%
0.3 49
 
0.2%
0.4 48
 
0.2%
0.06 43
 
0.2%
0.2 40
 
0.2%
0.41 39
 
0.2%
0.09 37
 
0.2%
0.29 37
 
0.2%
Other values (58) 935
 
4.0%
ValueCountFrequency (%)
0 21795
94.1%
0.05 2
 
< 0.1%
0.06 43
 
0.2%
0.07 72
 
0.3%
0.08 18
 
0.1%
0.09 37
 
0.2%
0.1 22
 
0.1%
0.11 20
 
0.1%
0.12 27
 
0.1%
0.13 32
 
0.1%
ValueCountFrequency (%)
0.8 3
< 0.1%
0.78 4
< 0.1%
0.76 1
 
< 0.1%
0.75 2
< 0.1%
0.74 1
 
< 0.1%
0.7 1
 
< 0.1%
0.69 2
< 0.1%
0.66 3
< 0.1%
0.64 4
< 0.1%
0.63 1
 
< 0.1%

is_sale
Boolean

High correlation  Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size22.7 KiB
False
21795 
True
 
1356
ValueCountFrequency (%)
False 21795
94.1%
True 1356
 
5.9%
2025-04-12T16:24:09.226854image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

imp_count
Real number (ℝ)

Distinct29
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.5609261
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:09.598191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q310
95-th percentile17
Maximum31
Range30
Interquartile range (IQR)8

Descriptive statistics

Standard deviation5.4031661
Coefficient of variation (CV)0.8235371
Kurtosis1.6395687
Mean6.5609261
Median Absolute Deviation (MAD)3
Skewness1.286351
Sum151892
Variance29.194204
MonotonicityNot monotonic
2025-04-12T16:24:09.742281image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
1 3551
15.3%
2 2719
11.7%
3 2523
10.9%
4 2069
8.9%
5 1598
 
6.9%
6 1535
 
6.6%
7 1167
 
5.0%
9 1092
 
4.7%
8 1064
 
4.6%
11 920
 
4.0%
Other values (19) 4913
21.2%
ValueCountFrequency (%)
1 3551
15.3%
2 2719
11.7%
3 2523
10.9%
4 2069
8.9%
5 1598
6.9%
6 1535
6.6%
7 1167
 
5.0%
8 1064
 
4.6%
9 1092
 
4.7%
10 790
 
3.4%
ValueCountFrequency (%)
31 31
 
0.1%
29 29
 
0.1%
28 28
 
0.1%
26 52
 
0.2%
25 115
0.5%
24 67
 
0.3%
23 23
 
0.1%
22 66
 
0.3%
21 195
0.8%
20 80
0.3%

brand
Text

Distinct266
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:10.088868image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length30
Median length24
Mean length6.3466805
Min length2

Characters and Unicode

Total characters146932
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBoytone
2nd rowBoytone
3rd rowBoytone
4th rowBoytone
5th rowBoytone
ValueCountFrequency (%)
sony 3205
 
12.6%
samsung 1924
 
7.6%
apple 1771
 
7.0%
yamaha 721
 
2.8%
pioneer 559
 
2.2%
canon 528
 
2.1%
sandisk 505
 
2.0%
kenwood 458
 
1.8%
corsair 449
 
1.8%
nikon 449
 
1.8%
Other values (269) 14792
58.3%
2025-04-12T16:24:10.580542image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 13706
 
9.3%
o 12950
 
8.8%
e 11796
 
8.0%
a 9999
 
6.8%
S 8085
 
5.5%
i 7625
 
5.2%
s 6431
 
4.4%
l 5186
 
3.5%
r 5010
 
3.4%
p 4776
 
3.3%
Other values (53) 61368
41.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 146932
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 13706
 
9.3%
o 12950
 
8.8%
e 11796
 
8.0%
a 9999
 
6.8%
S 8085
 
5.5%
i 7625
 
5.2%
s 6431
 
4.4%
l 5186
 
3.5%
r 5010
 
3.4%
p 4776
 
3.3%
Other values (53) 61368
41.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 146932
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 13706
 
9.3%
o 12950
 
8.8%
e 11796
 
8.0%
a 9999
 
6.8%
S 8085
 
5.5%
i 7625
 
5.2%
s 6431
 
4.4%
l 5186
 
3.5%
r 5010
 
3.4%
p 4776
 
3.3%
Other values (53) 61368
41.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 146932
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 13706
 
9.3%
o 12950
 
8.8%
e 11796
 
8.0%
a 9999
 
6.8%
S 8085
 
5.5%
i 7625
 
5.2%
s 6431
 
4.4%
l 5186
 
3.5%
r 5010
 
3.4%
p 4776
 
3.3%
Other values (53) 61368
41.8%
Distinct908
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:10.827063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Length

Max length828
Median length468
Mean length323.0298
Min length44

Characters and Unicode

Total characters7478463
Distinct characters78
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf Systems
2nd rowStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf Systems
3rd rowStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf Systems
4th rowStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf Systems
5th rowStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf Systems
ValueCountFrequency (%)
111713
 
16.7%
home 11998
 
1.8%
audio 11172
 
1.7%
by 7717
 
1.2%
video 6327
 
0.9%
more 5633
 
0.8%
tvs 4957
 
0.7%
speakers 4903
 
0.7%
and 4856
 
0.7%
accessories 4835
 
0.7%
Other values (5532) 493102
73.9%
2025-04-12T16:24:11.292846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 751995
 
10.1%
644742
 
8.6%
s 558936
 
7.5%
o 495523
 
6.6%
r 483864
 
6.5%
, 386262
 
5.2%
a 381408
 
5.1%
t 360183
 
4.8%
i 320788
 
4.3%
c 239568
 
3.2%
Other values (68) 2855194
38.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 7478463
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 751995
 
10.1%
644742
 
8.6%
s 558936
 
7.5%
o 495523
 
6.6%
r 483864
 
6.5%
, 386262
 
5.2%
a 381408
 
5.1%
t 360183
 
4.8%
i 320788
 
4.3%
c 239568
 
3.2%
Other values (68) 2855194
38.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 7478463
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 751995
 
10.1%
644742
 
8.6%
s 558936
 
7.5%
o 495523
 
6.6%
r 483864
 
6.5%
, 386262
 
5.2%
a 381408
 
5.1%
t 360183
 
4.8%
i 320788
 
4.3%
c 239568
 
3.2%
Other values (68) 2855194
38.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 7478463
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 751995
 
10.1%
644742
 
8.6%
s 558936
 
7.5%
o 495523
 
6.6%
r 483864
 
6.5%
, 386262
 
5.2%
a 381408
 
5.1%
t 360183
 
4.8%
i 320788
 
4.3%
c 239568
 
3.2%
Other values (68) 2855194
38.2%

currency
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size181.0 KiB
USD
23151 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters69453
Distinct characters3
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSD
2nd rowUSD
3rd rowUSD
4th rowUSD
5th rowUSD

Common Values

ValueCountFrequency (%)
USD 23151
100.0%

Length

2025-04-12T16:24:11.406549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-12T16:24:11.479553image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
usd 23151
100.0%

Most occurring characters

ValueCountFrequency (%)
U 23151
33.3%
S 23151
33.3%
D 23151
33.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 69453
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 23151
33.3%
S 23151
33.3%
D 23151
33.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 69453
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 23151
33.3%
S 23151
33.3%
D 23151
33.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 69453
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 23151
33.3%
S 23151
33.3%
D 23151
33.3%

day_n
Categorical

Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size181.0 KiB
Tuesday
5573 
Wednesday
3949 
Thursday
3574 
Saturday
3112 
Monday
2995 
Other values (2)
3948 

Length

Max length9
Median length8
Mean length7.3300505
Min length6

Characters and Unicode

Total characters169698
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThursday
2nd rowFriday
3rd rowTuesday
4th rowTuesday
5th rowThursday

Common Values

ValueCountFrequency (%)
Tuesday 5573
24.1%
Wednesday 3949
17.1%
Thursday 3574
15.4%
Saturday 3112
13.4%
Monday 2995
12.9%
Friday 2407
10.4%
Sunday 1541
 
6.7%

Length

2025-04-12T16:24:11.583310image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-04-12T16:24:11.710044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
tuesday 5573
24.1%
wednesday 3949
17.1%
thursday 3574
15.4%
saturday 3112
13.4%
monday 2995
12.9%
friday 2407
10.4%
sunday 1541
 
6.7%

Most occurring characters

ValueCountFrequency (%)
d 27100
16.0%
a 26263
15.5%
y 23151
13.6%
u 13800
8.1%
e 13471
7.9%
s 13096
7.7%
T 9147
 
5.4%
r 9093
 
5.4%
n 8485
 
5.0%
S 4653
 
2.7%
Other values (7) 21439
12.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 169698
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
d 27100
16.0%
a 26263
15.5%
y 23151
13.6%
u 13800
8.1%
e 13471
7.9%
s 13096
7.7%
T 9147
 
5.4%
r 9093
 
5.4%
n 8485
 
5.0%
S 4653
 
2.7%
Other values (7) 21439
12.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 169698
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
d 27100
16.0%
a 26263
15.5%
y 23151
13.6%
u 13800
8.1%
e 13471
7.9%
s 13096
7.7%
T 9147
 
5.4%
r 9093
 
5.4%
n 8485
 
5.0%
S 4653
 
2.7%
Other values (7) 21439
12.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 169698
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
d 27100
16.0%
a 26263
15.5%
y 23151
13.6%
u 13800
8.1%
e 13471
7.9%
s 13096
7.7%
T 9147
 
5.4%
r 9093
 
5.4%
n 8485
 
5.0%
S 4653
 
2.7%
Other values (7) 21439
12.6%

month
Real number (ℝ)

High correlation 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.6510302
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:11.900323image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q16
median8
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.5928434
Coefficient of variation (CV)0.33888814
Kurtosis-0.62885918
Mean7.6510302
Median Absolute Deviation (MAD)2
Skewness-0.099417331
Sum177129
Variance6.7228368
MonotonicityNot monotonic
2025-04-12T16:24:12.014946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
8 5004
21.6%
7 4116
17.8%
3 2517
10.9%
12 2474
10.7%
5 2127
9.2%
9 1977
 
8.5%
10 1859
 
8.0%
6 1448
 
6.3%
11 1264
 
5.5%
4 357
 
1.5%
ValueCountFrequency (%)
1 8
 
< 0.1%
3 2517
10.9%
4 357
 
1.5%
5 2127
9.2%
6 1448
 
6.3%
7 4116
17.8%
8 5004
21.6%
9 1977
 
8.5%
10 1859
 
8.0%
11 1264
 
5.5%
ValueCountFrequency (%)
12 2474
10.7%
11 1264
 
5.5%
10 1859
 
8.0%
9 1977
 
8.5%
8 5004
21.6%
7 4116
17.8%
6 1448
 
6.3%
5 2127
9.2%
4 357
 
1.5%
3 2517
10.9%

month_n
Categorical

High correlation 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size181.0 KiB
August
5004 
July
4116 
March
2517 
December
2474 
May
2127 
Other values (6)
6913 

Length

Max length9
Median length7
Mean length5.7793184
Min length3

Characters and Unicode

Total characters133797
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDecember
2nd rowSeptember
3rd rowOctober
4th rowAugust
5th rowSeptember

Common Values

ValueCountFrequency (%)
August 5004
21.6%
July 4116
17.8%
March 2517
10.9%
December 2474
10.7%
May 2127
9.2%
September 1977
 
8.5%
October 1859
 
8.0%
June 1448
 
6.3%
November 1264
 
5.5%
April 357
 
1.5%

Length

2025-04-12T16:24:12.154746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
august 5004
21.6%
july 4116
17.8%
march 2517
10.9%
december 2474
10.7%
may 2127
9.2%
september 1977
 
8.5%
october 1859
 
8.0%
june 1448
 
6.3%
november 1264
 
5.5%
april 357
 
1.5%

Most occurring characters

ValueCountFrequency (%)
e 19188
14.3%
u 15580
 
11.6%
r 10456
 
7.8%
t 8840
 
6.6%
b 7574
 
5.7%
c 6850
 
5.1%
y 6251
 
4.7%
m 5715
 
4.3%
J 5572
 
4.2%
A 5361
 
4.0%
Other values (15) 42410
31.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 133797
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 19188
14.3%
u 15580
 
11.6%
r 10456
 
7.8%
t 8840
 
6.6%
b 7574
 
5.7%
c 6850
 
5.1%
y 6251
 
4.7%
m 5715
 
4.3%
J 5572
 
4.2%
A 5361
 
4.0%
Other values (15) 42410
31.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 133797
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 19188
14.3%
u 15580
 
11.6%
r 10456
 
7.8%
t 8840
 
6.6%
b 7574
 
5.7%
c 6850
 
5.1%
y 6251
 
4.7%
m 5715
 
4.3%
J 5572
 
4.2%
A 5361
 
4.0%
Other values (15) 42410
31.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 133797
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 19188
14.3%
u 15580
 
11.6%
r 10456
 
7.8%
t 8840
 
6.6%
b 7574
 
5.7%
c 6850
 
5.1%
y 6251
 
4.7%
m 5715
 
4.3%
J 5572
 
4.2%
A 5361
 
4.0%
Other values (15) 42410
31.7%

day
Real number (ℝ)

Distinct31
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.693879
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:12.284434image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median16
Q324
95-th percentile30
Maximum31
Range30
Interquartile range (IQR)17

Descriptive statistics

Standard deviation9.6816219
Coefficient of variation (CV)0.61690432
Kurtosis-1.3318379
Mean15.693879
Median Absolute Deviation (MAD)8
Skewness0.032258252
Sum363329
Variance93.733802
MonotonicityNot monotonic
2025-04-12T16:24:12.427835image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 2151
 
9.3%
18 1581
 
6.8%
10 1486
 
6.4%
4 1279
 
5.5%
30 1154
 
5.0%
26 1112
 
4.8%
9 1111
 
4.8%
6 967
 
4.2%
31 962
 
4.2%
22 903
 
3.9%
Other values (21) 10445
45.1%
ValueCountFrequency (%)
1 2151
9.3%
2 174
 
0.8%
3 404
 
1.7%
4 1279
5.5%
5 295
 
1.3%
6 967
4.2%
7 626
 
2.7%
8 779
 
3.4%
9 1111
4.8%
10 1486
6.4%
ValueCountFrequency (%)
31 962
4.2%
30 1154
5.0%
29 849
3.7%
28 871
3.8%
27 240
 
1.0%
26 1112
4.8%
25 434
 
1.9%
24 880
3.8%
23 729
3.1%
22 903
3.9%

week_number
Real number (ℝ)

High correlation 

Distinct42
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.34275
Minimum1
Maximum51
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:12.586145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10
Q123
median32
Q338
95-th percentile49
Maximum51
Range50
Interquartile range (IQR)15

Descriptive statistics

Standard deviation11.316498
Coefficient of variation (CV)0.36105632
Kurtosis-0.64802703
Mean31.34275
Median Absolute Deviation (MAD)7
Skewness-0.26698013
Sum725616
Variance128.06312
MonotonicityNot monotonic
2025-04-12T16:24:12.763769image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
49 2330
 
10.1%
35 1680
 
7.3%
30 1539
 
6.6%
31 1356
 
5.9%
22 1140
 
4.9%
29 1102
 
4.8%
34 1088
 
4.7%
9 893
 
3.9%
33 811
 
3.5%
38 799
 
3.5%
Other values (32) 10413
45.0%
ValueCountFrequency (%)
1 4
 
< 0.1%
2 1
 
< 0.1%
3 1
 
< 0.1%
4 2
 
< 0.1%
9 893
3.9%
10 589
2.5%
11 258
 
1.1%
12 107
 
0.5%
13 670
2.9%
14 323
 
1.4%
ValueCountFrequency (%)
51 2
 
< 0.1%
50 142
 
0.6%
49 2330
10.1%
46 759
 
3.3%
45 432
 
1.9%
44 202
 
0.9%
43 614
 
2.7%
42 332
 
1.4%
41 784
 
3.4%
39 122
 
0.5%

price_std
Real number (ℝ)

High correlation 

Distinct1792
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean61.992819
Minimum0.004472136
Maximum1423.9021
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size181.0 KiB
2025-04-12T16:24:12.931239image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0.004472136
5-th percentile1.8575655
Q17.7711035
median18.764962
Q359.176162
95-th percentile263.26699
Maximum1423.9021
Range1423.8976
Interquartile range (IQR)51.405059

Descriptive statistics

Standard deviation125.49513
Coefficient of variation (CV)2.0243494
Kurtosis30.958918
Mean61.992819
Median Absolute Deviation (MAD)14.565739
Skewness4.8577929
Sum1435195.8
Variance15749.027
MonotonicityNot monotonic
2025-04-12T16:24:13.111590image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
96.10393034 114
 
0.5%
902.0815262 106
 
0.5%
147.8285273 93
 
0.4%
4.939190662 91
 
0.4%
263.2669851 84
 
0.4%
169.5397495 82
 
0.4%
13.03758952 74
 
0.3%
82.35379009 72
 
0.3%
150.2127133 70
 
0.3%
6.107178585 68
 
0.3%
Other values (1782) 22297
96.3%
ValueCountFrequency (%)
0.004472135955 5
< 0.1%
0.005 9
< 0.1%
0.005 9
< 0.1%
0.005163977795 6
< 0.1%
0.005477225575 5
< 0.1%
0.01603567451 8
< 0.1%
0.02065591118 6
< 0.1%
0.02065591118 10
< 0.1%
0.02121320344 2
 
< 0.1%
0.0219089023 6
< 0.1%
ValueCountFrequency (%)
1423.902118 10
 
< 0.1%
1314.777842 16
 
0.1%
1086.316794 10
 
< 0.1%
1059.238887 2
 
< 0.1%
1003.999705 2
 
< 0.1%
913.0534851 6
 
< 0.1%
905.3261206 14
 
0.1%
902.0815262 106
0.5%
887.5773053 5
 
< 0.1%
887.0663792 27
 
0.1%

Interactions

2025-04-12T16:24:02.934849image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:46.848052image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:48.677269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:50.554401image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:52.808344image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:54.490600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:56.547862image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:58.455799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:59.910059image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:01.420236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:03.084160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:46.988897image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:48.880335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:50.726660image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:52.945969image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:54.739653image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:56.800500image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:58.592406image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:00.067002image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:01.549261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:03.219728image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:47.203861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:49.099994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:50.857418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:53.085350image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:54.955537image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:56.990523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:58.755328image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:00.196205image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:01.678490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:03.355225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:47.351914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:49.271318image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:50.990380image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:53.216867image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:55.161428image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:57.410541image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:58.946372image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:00.328829image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:01.803523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:03.490421image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:47.506127image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:49.418252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:51.132079image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:53.355118image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:55.357291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:57.553730image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:59.129605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:00.458848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:01.932807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:03.636269image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:47.677286image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:49.626436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:52.034378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:53.519041image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:55.553567image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:57.705557image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:59.274722image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:00.600225image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:02.072183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:03.775491image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:47.854000image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:49.870547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:52.193647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:53.714181image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:55.740391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:57.874560image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:59.400713image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:00.735790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:02.200193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:03.905726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:48.010369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:50.006750image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:52.336946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:53.863669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:55.926683image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:58.027678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:59.520999image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:00.897837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:02.327085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:04.042019image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:48.177529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:50.174041image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:52.513962image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:54.074719image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:56.142309image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:58.179572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:59.649371image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:01.153520image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:02.456253image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:04.175256image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:48.348077image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:50.315369image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:52.667211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:54.285549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:56.330351image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:58.310827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:23:59.774618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:01.282407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-04-12T16:24:02.576252image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-04-12T16:24:13.262454image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
clusterdayday_ndisc_percentagedisc_priceimp_countis_salemerchantmonthmonth_npriceprice_stdunnamed: 0week_number
cluster1.000-0.0140.033-0.068-0.1750.0130.1190.1050.0210.069-0.178-0.1250.0870.020
day-0.0141.0000.3550.0210.033-0.0880.1920.301-0.0800.3480.0350.0090.0210.032
day_n0.0330.3551.0000.0520.0180.0420.1270.1650.3280.3460.0170.0320.0190.313
disc_percentage-0.0680.0210.0521.0000.010-0.1590.9460.2110.1370.0700.0710.0270.0180.130
disc_price-0.1750.0330.0180.0101.000-0.0160.0660.0920.0410.0710.9970.7930.0320.043
imp_count0.013-0.0880.042-0.159-0.0161.0000.1450.153-0.1840.086-0.026-0.061-0.015-0.191
is_sale0.1190.1920.1270.9460.0660.1451.0000.5500.1880.2070.1790.1060.0600.236
merchant0.1050.3010.1650.2110.0920.1530.5501.0000.3630.3730.0980.1030.0920.373
month0.021-0.0800.3280.1370.041-0.1840.1880.3631.0001.0000.0500.0280.0150.990
month_n0.0690.3480.3460.0700.0710.0860.2070.3731.0001.0000.0670.0620.0480.869
price-0.1780.0350.0170.0710.997-0.0260.1790.0980.0500.0671.0000.7920.0340.052
price_std-0.1250.0090.0320.0270.793-0.0610.1060.1030.0280.0620.7921.0000.0590.029
unnamed: 00.0870.0210.0190.0180.032-0.0150.0600.0920.0150.0480.0340.0591.0000.013
week_number0.0200.0320.3130.1300.043-0.1910.2360.3730.9900.8690.0520.0290.0131.000

Missing values

2025-04-12T16:24:04.424850image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-04-12T16:24:04.686431image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

unnamed: 0date_imp_dclustercategory_namenamepricedisc_pricemerchantconditiondisc_percentageis_saleimp_countbrandp_descriptioncurrencyday_nmonthmonth_ndayweek_numberprice_std
042017-12-1435speaker, portable, bluetoothBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond69.0064.99Walmart.comNew0.06Yes1BoytoneStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf SystemsUSDThursday12December14503.880725
152017-09-0835speaker, portable, bluetoothBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond69.0069.00Walmart.comNew0.00No1BoytoneStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf SystemsUSDFriday9September8363.880725
262017-10-2435speaker, portable, bluetoothBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond66.0066.00Walmart.comNew0.00No1BoytoneStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf SystemsUSDTuesday10October24433.880725
372017-08-1535speaker, portable, bluetoothBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond74.9974.99Walmart.comNew0.00No1BoytoneStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf SystemsUSDTuesday8August15333.880725
482017-09-1435speaker, portable, bluetoothBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond69.9969.99Walmart.comNew0.00No1BoytoneStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf SystemsUSDThursday9September14373.880725
592017-07-2335speaker, portable, bluetoothBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond64.9964.99Walmart.comNew0.00No1BoytoneStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf SystemsUSDSunday7July23293.880725
6102017-10-1035speaker, portable, bluetoothBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond69.9969.99Bestbuy.comNew0.00No1BoytoneStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf SystemsUSDTuesday10October10411.355764
7112017-08-2835speaker, portable, bluetoothBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond66.9966.99Bestbuy.comNew0.00No1BoytoneStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf SystemsUSDMonday8August28351.355764
8122017-08-1235speaker, portable, bluetoothBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond65.9965.99Bestbuy.comNew0.00No1BoytoneStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf SystemsUSDSaturday8August12321.355764
9132017-08-0135speaker, portable, bluetoothBoytone - 2500W 2.1-Ch. Home Theater System - Black Diamond64.9964.99Bestbuy.comNew0.00No12BoytoneStereos,Portable Bluetooth Speakers,TV, Video & Home Audio,Speaker Systems,Portable Audio & Video,Electronics,See more Black BOYTONE Bt-210f 30 Watt FM Radio Bluetoo...,Speakers,Home Audio & Theater,All Home Speakers,Consumer Electronics,See more BOYTONE Bt-210f Bluetooth Wireless Speaker Mp3...,Home Theater Systems,MP3 Player Accessories,Home Audio,Audio,Cell,Stereo Shelf SystemsUSDTuesday8August1311.355764
unnamed: 0date_imp_dclustercategory_namenamepricedisc_pricemerchantconditiondisc_percentageis_saleimp_countbrandp_descriptioncurrencyday_nmonthmonth_ndayweek_numberprice_std
23141295832017-10-1025sound, speaker, homenaxa - 2.1-Channel Soundbar with 50-Watt Digital Amplifier - Black58.9958.99Bestbuy.comNew0.00No6naxaTVs & Electronics,Computers,Home Theater & Audio,Computer Accessories,Speaker Systems,Frys,Electronics,Sound Bars,Speakers,Portable Audio,Home Audio & Theater,All Home Speakers,Home Theater Systems,Home Audio,Audio,Computer Speakers,MP3 AccessoriesUSDTuesday10October104134.396428
23142295842017-09-0625sound, speaker, homenaxa - 2.1-Channel Soundbar with 50-Watt Digital Amplifier - Black58.9958.99Bestbuy.comNew0.00No6naxaTVs & Electronics,Computers,Home Theater & Audio,Computer Accessories,Speaker Systems,Frys,Electronics,Sound Bars,Speakers,Portable Audio,Home Audio & Theater,All Home Speakers,Home Theater Systems,Home Audio,Audio,Computer Speakers,MP3 AccessoriesUSDWednesday9September63634.396428
23143295852017-09-1825sound, speaker, homenaxa - 2.1-Channel Soundbar with 50-Watt Digital Amplifier - Black58.9958.99Bestbuy.comNew0.00No6naxaTVs & Electronics,Computers,Home Theater & Audio,Computer Accessories,Speaker Systems,Frys,Electronics,Sound Bars,Speakers,Portable Audio,Home Audio & Theater,All Home Speakers,Home Theater Systems,Home Audio,Audio,Computer Speakers,MP3 AccessoriesUSDMonday9September183834.396428
23144295862017-08-3025sound, speaker, homenaxa - 2.1-Channel Soundbar with 50-Watt Digital Amplifier - Black58.9958.99Bestbuy.comNew0.00No6naxaTVs & Electronics,Computers,Home Theater & Audio,Computer Accessories,Speaker Systems,Frys,Electronics,Sound Bars,Speakers,Portable Audio,Home Audio & Theater,All Home Speakers,Home Theater Systems,Home Audio,Audio,Computer Speakers,MP3 AccessoriesUSDWednesday8August303534.396428
23145295872017-06-0125sound, speaker, homenaxa - 2.1-Channel Soundbar with 50-Watt Digital Amplifier - Black58.9958.99Bestbuy.comNew0.00No6naxaTVs & Electronics,Computers,Home Theater & Audio,Computer Accessories,Speaker Systems,Frys,Electronics,Sound Bars,Speakers,Portable Audio,Home Audio & Theater,All Home Speakers,Home Theater Systems,Home Audio,Audio,Computer Speakers,MP3 AccessoriesUSDThursday6June12234.396428
23146295882017-06-0125sound, speaker, homenaxa - 2.1-Channel Soundbar with 50-Watt Digital Amplifier - Black58.9958.99Bestbuy.comNew0.00No6naxaTVs & Electronics,Computers,Home Theater & Audio,Computer Accessories,Speaker Systems,Frys,Electronics,Sound Bars,Speakers,Portable Audio,Home Audio & Theater,All Home Speakers,Home Theater Systems,Home Audio,Audio,Computer Speakers,MP3 AccessoriesUSDThursday6June12234.396428
23147295892017-08-1525sound, speaker, homenaxa - 2.1-Channel Soundbar with 50-Watt Digital Amplifier - Black63.9958.49Walmart.comNew0.09Yes2naxaTVs & Electronics,Computers,Home Theater & Audio,Computer Accessories,Speaker Systems,Frys,Electronics,Sound Bars,Speakers,Portable Audio,Home Audio & Theater,All Home Speakers,Home Theater Systems,Home Audio,Audio,Computer Speakers,MP3 AccessoriesUSDTuesday8August153311.434096
23148295902017-07-2325sound, speaker, homenaxa - 2.1-Channel Soundbar with 50-Watt Digital Amplifier - Black63.9958.49Walmart.comNew0.09Yes2naxaTVs & Electronics,Computers,Home Theater & Audio,Computer Accessories,Speaker Systems,Frys,Electronics,Sound Bars,Speakers,Portable Audio,Home Audio & Theater,All Home Speakers,Home Theater Systems,Home Audio,Audio,Computer Speakers,MP3 AccessoriesUSDSunday7July232911.434096
23149295912017-11-1225sound, speaker, homenaxa - 2.1-Channel Soundbar with 50-Watt Digital Amplifier - Black81.5281.52Walmart.comNew0.00No1naxaTVs & Electronics,Computers,Home Theater & Audio,Computer Accessories,Speaker Systems,Frys,Electronics,Sound Bars,Speakers,Portable Audio,Home Audio & Theater,All Home Speakers,Home Theater Systems,Home Audio,Audio,Computer Speakers,MP3 AccessoriesUSDSunday11November124511.434096
23150295922017-12-1425sound, speaker, homenaxa - 2.1-Channel Soundbar with 50-Watt Digital Amplifier - Black58.9958.99Walmart.comNew0.00No1naxaTVs & Electronics,Computers,Home Theater & Audio,Computer Accessories,Speaker Systems,Frys,Electronics,Sound Bars,Speakers,Portable Audio,Home Audio & Theater,All Home Speakers,Home Theater Systems,Home Audio,Audio,Computer Speakers,MP3 AccessoriesUSDThursday12December145011.434096